你在听我说话吗？微调聊天机器人以实现共情对话
Are You Listening to Me? Fine-Tuning Chatbots for Empathetic Dialogue
AI总结：
本文研究大型语言模型在共情对话生成中的表现，通过ChatGPT和Gemini扩展专家数据集并结合VADER情感分析与人工评估，发现情感建模需兼顾结构对齐与定性深度。
摘要：
自ELIZA以来，对话智能体已取得显著进展，其角色扩展到医疗保健、教育和客户服务等多个领域。随着这些智能体日益融入日常人际互动，对情商，尤其是共情倾听的需求变得越来越重要。在本研究中，我们探讨了大型语言模型（LLMs）在被要求生成情感丰富的互动时的表现。从一个由专家手工制作、用于反映共情行为的小型数据集出发，我们使用两种LLM——ChatGPT和Gemini——扩展了对话。我们利用情感分析（通过VADER）和专家评估分析了对话的情感进展。虽然生成的对话通常反映了预期的情感结构，但人工评估揭示了在感知到的共情和响应连贯性方面的重要差异。这些发现表明，对话中的情感建模不仅需要所表达情感的结构对齐，还需要定性深度，这凸显了在开发具备情感能力的智能体时结合自动化方法和以人为中心的方法的重要性。
英文摘要：
Conversational agents have made significant progress since ELIZA, expanding their role across various domains, including healthcare, education, and customer service. As these agents become increasingly integrated into daily human interactions, the need for emotional intelligence, particularly empathetic listening, becomes increasingly essential. In this study, we explore how Large Language Models (LLMs) respond when tasked with generating emotionally rich interactions. Starting from a small dataset manually crafted by an expert to reflect empathic behavior, we extended the conversations using two LLMs: ChatGPT and Gemini. We analyzed the emotional progression of the dialogues using both sentiment analysis (via VADER) and expert assessments. While the generated conversations often mirrored the intended emotional structure, human evaluation revealed important differences in the perceived empathy and coherence of the responses. These findings suggest that emotion modeling in dialogues requires not only structural alignment in the expressed emotions but also qualitative depth, highlighting the importance of combining automated and humancentered methods in the development of emotionally competent agents.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
